Post on 22-Apr-2020
26th – 29th March 2018
Module 3Indicator 11.3.1 Land Consumption Rate to Population
Growth Rate
Dennis Mwaniki
Global Urban Observatory,
Research and Capacity Development Branch, UN-Habitat
26th – 29th March 2018
Bangkok, Thailand
Regional Training Workshop on Human Settlement Indicators
26th – 29th March 2018
TARGET 11.3: By 2030, enhance inclusive and sustainable urbanization and capacity for participatory, integrated and sustainable human settlement planning and management in all countries.
Indicator 11.3.1: RATIO OF LAND CONSUMPTION RATE TO POPULATION GROWTH RATE
Tier II indicator
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Outline
• Rationale for monitoring indicator
• Indicator components
• Definition of concepts
• Computation
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Why monitor
• Need to understand why cities grow – is it just a factor of population? • Start answering some questions from CPI monitoring – why do some cities grow more sustainably than others?
• How does city growth affect regional development, policies, and actions? E.g sprawl and regional policies
• To understand “speed of transition” and where growth is happening spatially –• key components of urban challenges diagnosis and for making of informed decisions on both urban growth and
development control.
• Majority of urban growth is happening in emerging small towns with populations of less than 500,000 people; big towns are also growing fast (UN-Habitat, 2010) – what kind of growth is this? Compact or dispersed?
• Informs investment – compactness versus dispersal have different investment implications
• Data will help development of practical international guidelines, that are locally applicable
• Data will help monitor vulnerability and appropriately prepare for disaster response - such as urban disasters related to rapid settlement in environmentally sensitive areas.
• Understanding land consumption cultures (historical) inform spatial planning, help protect environmental, social and economic resources and help project land demand for urban growth.
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• Land consumption rate – the annual rate at which cities uptake land for urbanized
uses (both built-up and open space demands)
• Population growth rate - the change in population in a given area over a unit period
of time; expressed as a percentage of the number of individuals in the population at
the beginning of that period
Reporting
• Monitoring to be repeated at regular intervals of 5 years
• Data collection will be at the city, used to develop national, regional, global aggregates
Indicator Components and Reporting
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• City – the urban extent as defined by the functional, spatially delimited boundaries
• Built up area – the contiguous part of a city occupied by buildings and other
impervious surfaces
• Non-built up area – the part of a city that is not occupied by buildings and other
impervious surfaces. This includes sub-divided and non-divided land, public spaces,
developable and undevelopable land within the city limits.
Definition of concepts
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• National Statistical Agencies • Custodians of statistical data in countries - Source of population data
• Reference authority for data disaggregation, interpolation/extrapolation
• UNDESA - Global Urbanization Prospects initiative.
• City/ country high resolution imagery • Country based sensors ; High resolution commercial imagery through partnership with providers
• The preferred option for indicator computation – where they exist
• Open source Imagery Platforms• Landsat – NASA; 16 days return period ; average 30m spatial resolution
• Sentinel 2– European Space Agency ; 5 day return period, average 20m spatial resolution
• Google Earth –medium to high resolution free imagery
• Analytical databases • Global Human Settlements Layer (GHSL), EC/JRC varied data from 1975 – 2016
• Atlas of urban expansion, NYU, UN-Habitat, Lincoln Institute
• Global Urban Footprint (German Aerospace Center)
• Gridded Population of the World (GPW)
• Degree of Urbanization Global Human Settlement Grid
Most open source platforms offer good starting point for data collection
Some Data Sources
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• Current method, as defined by published metadata has limitations
• Proposals on upgrade have been – still under discussion and receiving country inputs
The Method
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• Decide the two years for which the indicator should be computed – usually, 5 to 10 year intervals
• Using spatial metrics, delimit functional city boundary for the two years
• Collect/generate population data for each of the years – interpolate/extrapolate to year and functional city boundary
• Compute indicator
• Example application:
• Ho Chi Minh City, Vietnam
• Computation for Ho Chi Minh City years 1989 – 1999 - 2015
Generic steps for current method
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Step 1: Delimit functional city area
Download imagery from usgs, sentinel or use high resolution city/country imagery
Undertake supervised imagery classification in image processing/ GIS software – classes can include built-up areas, open spaces, water etc
Buffer urban pixels to 100m to attain fringe open space area
Gap fill to attain continuous urban boundary and compute area using geometry tools in GIS or alternative statistical methods
Undertake spatial statistics analysis to distinguish between urban and rural pixels
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Step 2: Collect/Generate population data
• Population growth rate may be easier to measure from years’ of experience and monitoring. General formula applies
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(�)
• But how do we disaggregate population where a spatially functional city boundary partially includes an Enumeration area?
• Preferred method is to re-compute population using household level data, but this may not
always be possible in all countries
• Other options
• Population density for EA - which is multiplied by land area of “included” part of EA
• Built-up pixel density for EA – which is multiplied by number of built-up pixels in
“included” part of EA
• Built-up pixels helps redistribute population based on settled areas but does not account for built-
up land use variations
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Proposed approach on spatial disaggregation of population
- Using Enumeration areas as defined by NSAs
- Calculate area covered by Built-up pixels within EA
- Divide EA population by built-up area = No. of people/Built-up pixel
- Multiply built up density by partial EA size to attain population
Spatial disaggregation of population data
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Compute Land consumption rate for years A - B
• ��� =
�� ������/����
(�)
Where
• Urbt
Urban extent in km2 for the initial year
• Urbt+n
Urban extent in km2 for current year
• y number of years between the two measurement periods
Compute Population Growth Rate (PGR) for years A - B
• ��� =
�� �����/���
(�)
Where
• PoptTotal population within the urban extent in
initial year
• Popt+n
Total population within the urban extent current year
• y Number of years between the two measurement periods
Step 3: Compute Indicator
Compute the ratio of land consumption rate to population growth rate (LCRPGR)
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Thus ������ =
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�� ����� ��
�
26th – 29th March 2018
• Approach to land consumption concept is to simplistic for actual urban growth dynamics (internal reflections)
• Approach captures only the urban extent change, nothing on internal city dynamics
• How do we know when cities lose some of their area due to disasters, natural catastrophes? (Corbane et al, 2017)
• Cities grow in multiple ways, why capture only one?
• Infill - built-up areas added during a growth period that occupy urbanized open space within the urban extent of the earlier year
• Extension - built up areas added during the growth period that constitute contigousurban clusters that are attached to the urban extent in the earlier period
• Leapfrogging - built up areas added in the new period that constitute new contiguous urban clusters that are not attached to the urban extent of the earlier period
• Inclusion covers the added areas that existed at the previous time period but were outside the urban extent of the previous time period. (do not constitute new development)
Methodological limitations
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• Mix of both external and internal city growth
• Simplified version
• Measure the amount of land consumed by outwards city expansion between years
Total urban extent land coverage in year B [minus] Total urban extent land coverage in year A
• Measure amount of land consumed by internal city growth between years
Total built-up area in year B [minus] Total built-up area in year A
• External growth measures both newly built areas and open spaces as defined by urban extent
• Internal growth measures change of land from open space to built up within the same boundaries E.g replacement of open spaces by buildings, or vice versa.
Method: Proposed Modification to method
Compute Land consumption rate
between target years
��� =
��(���������� )�(�����/��� )
(�)
Where
• Urbt
Urban extent in km2 for the
initial year
• Urbt+n
Urban extent in km2 for
current year
• y number of years between the
two measurement periods
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COMPUTATION APPLICATION
HO CHI MINH CITY, VIETNAM
Computation Years: 1989 – 1999
1999- 2015
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Calculation: External Growth
Urban extent size (Sq.Km)
1989= 84.537
1999= 224.883
2015= 1037.286
.
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Calculation: Internal Growth
Built Up Area 1989 = 53.7768
Built Up Area 2015 = 79.9101
Urban extent Area
1989 = 84.537
City Built Up Area 1999 = 77.1615
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Indicator Computation
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What do the numbers mean?
• Above 1: Faster growth of land consumption than population
• Above 1: Faster population growth than city land uptake
• How does this affect urbanization policy at the local, national and global levels
• What do numbers say about global urbanization trends?
• What decisions can we make on regional/ cross-border development guidelines?
Linkage between land and population creates a new level of interesting data to aid urban management
Results Interpretation, Use
26th – 29th March 2018
• We are still discussing and finalizing methodology
• would you like to help us refine it? Please sign up for joint piloting, local level interpretation
• Next Expert Group Meeting to discuss methods – May 2018
• Projected rapid adoption by cities
Conclusion
26th – 29th March 2018
THANK YOU
dennis.mwaniki@un.org